DocumentCode :
1400939
Title :
Probabilistic Template-Based Chord Recognition
Author :
Oudre, Laurent ; Févotte, Cédric ; Grenier, Yves
Author_Institution :
TELECOM ParisTech, Paris, France
Volume :
19
Issue :
8
fYear :
2011
Firstpage :
2249
Lastpage :
2259
Abstract :
This paper describes a probabilistic approach to template-based chord recognition in music signals. The algorithm only takes chromagram data and a user-defined dictionary of chord templates as input data. No training or musical information such as key, rhythm, or chord transition models is required. The chord occurrences are treated as probabilistic events, whose probabilities are learned from the song using an expectation-maximization (EM) algorithm. The adaptative estimation of these probabilities (together with an ad-hoc postprocessing filtering) has the desirable effect of smoothing out spurious chords that would occur in our previous baseline work. Our algorithm is compared to various methods that entered the Music Information Retrieval Evaluation eXchange (MIREX) in 2008 and 2009, using a diverse set of evaluation metrics, some of which are new. The systems are tested on two evaluation corpuses; the first one is composed of the Beatles catalog (180 pop-rock songs) and the other one is constituted of 20 songs from various artists and music genres. Results show that our method outperforms state-of-the-art chord recognition systems.
Keywords :
expectation-maximisation algorithm; information retrieval; music; probability; signal representation; Beatles catalog; ad-hoc postprocessing filtering; adaptative estimation; chord recognition; chord templates; chord transition; chromagram data; expectation-maximization; music information retrieval evaluation exchange; music signals; probabilistic events; probabilistic template; user-defined dictionary; Dictionaries; Harmonic analysis; Hidden Markov models; Multiple signal classification; Probabilistic logic; Training; Vocabulary; Chord recognition; music information retrieval (MIR); music signal processing; music signal representation;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2010.2098870
Filename :
5664772
Link To Document :
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